code: def test_consume_dense_wrong_dims(datadir):
      model = onnx.load(datadir.file("keras_linear_131.onnx"))
      parser = NetworkParser()
      parser.parse_network(model.graph, None, None)
  
      parser._nodes[
          "StatefulPartitionedCall/keras_linear_131/dense/MatMul"
      ][1].input.append("abcd")
      with pytest.raises(ValueError) as excinfo:
          parser._consume_dense_nodes(
              parser._nodes[
                  "StatefulPartitionedCall/keras_linear_131/dense/MatMul"
              ][1],
              parser._nodes[
                  "StatefulPartitionedCall/keras_linear_131/dense/MatMul"
              ][2],
          )
      expected_msg_dense = "StatefulPartitionedCall/keras_linear_131/dense/MatMul input has 3 dimensions, only nodes with 2 input dimensions can be used as starting points for consumption."
      assert str(excinfo.value) == expected_msg_dense
  
file_path: OMLT/tests/io/test_onnx_parser.py
imports: import pytest
  from omlt.dependencies import onnx, onnx_available
label_desc: Use image node_id 12 for calling a global function with example usage: test_consume_dense_wrong_dims(datadir) without return types